The accurate detection and measurement of radiation, vibration or other types of energy are employed in many industries, including homeland security, scientific instrumentation, medical imaging, materials analysis, meteorology, information and communication technology (ICT), and the mineral processing industry. These and other industries use such detection and measurement to analyze materials, structures, products, information, signals or other specimens. Transmission based imaging, spectroscopic analysis or other modalities can be used to perform such analysis.
In mineral and oil exploration, borehole logging techniques use gamma-rays and neutrons to determine the subsurface composition of rocks and mineral deposits. Data on the porosity and density of rock formations can be determined from nuclear borehole logging techniques, and this is then used to help detect the presence of geological reservoirs and their contents (e.g., oil, gas or water).
SONAR (sound navigation and ranging) is commonly used in navigation and for locating objects within a body of water. SODAR, or sonic detection and ranging, can be used to measure the scattering of sound waves by atmospheric turbulence and, for example, to measure wind speed at various heights above the ground, and the thermodynamic structure of the lower layer of the atmosphere.
Ultrasound may be used for medical imaging or other purposes, such as to form images of foetuses, to find locate flaws in or measure the thickness of certain types of objects, or to locate objects in real-time (in manufacturing environments, for example).
Spectroscopy is commonly used to analyze materials. Knowledge about a material can be obtained by analysis of radiation emission from or absorption by elements within the specimen. The emission of radiation can be stimulated emission due to some form of incident radiation or natural emission from the constituent elements.
Two standard stimulated emission spectroscopy techniques are X-ray fluorescence (XRF) and Particle-induced X-ray emission (PIXE). These techniques are used in the analysis of materials in the ICT and minerals exploration and processing industries. In these techniques, knowledge of the material is obtained by detection and analysis of secondary (or fluorescent) X-rays emitted from the material after that material has been energized by stimulation with high energy photons or particles.
Gamma-ray spectroscopy, for example, is a form of spectroscopy in which the emitted electromagnetic radiation is in the form of gamma-rays. In gamma-ray spectroscopy the detection of gamma rays is commonly performed with a scintillation crystal (such as thallium-activated sodium iodide, NaI(TI)), though there are a number of other detector types that can also be used. NaI(TI) crystals generate ultra-violet photons pursuant to incident gamma-ray radiation. These photons are then received by a photomultiplier tube (PMT) which generates a corresponding electrical signal or pulse. As a result, the interaction between the photons and the detector gives rise to pulse-like signals, the shape of which is determined by the incident gamma-ray radiation, the detecting crystal and the PMT. The fundamental form of these pulse-like signals is referred to as the impulse response of the detector.
The output from the photomultiplier is an electrical signal representing the summation of input signals, of determined form, generated in response to discrete gamma rays arriving at the scintillation crystal. By analysing the detector output over time, and in particular the amplitudes of the component signals, it is possible to deduce information regarding the chemical composition of the material being analysed.
Analysis by gamma-ray spectroscopy requires the characterization of the individual pulse-like signals generated in response to incident gamma-rays. Signal parameters of particular interest include signal amplitude, number and time of occurrence or temporal position (whether measured as time of arrival, time of maximum or otherwise). If the arrival times of two gamma-rays differ by more than the response time of the detector, analysis of the detector output is relatively straightforward. However, in many applications a high flux of gamma-rays cannot be avoided, or may be desirable so that spectroscopic analysis can be performed in a reasonable time period. As the time between the arrivals of gamma-rays decreases, characterization of all resultant signals becomes difficult.
In particular, the analysis is affected by a phenomenon known as pulse pile-up [see, for example, G. F. Knoll, Radiation Detection and Measurement, 3rd edition, Chapter 17, pp. 632-634, 658 and 659, John Wiley and Sons, New York 2000], whereby multiple gamma-rays arriving more or less simultaneously produce signals which sum together and may be inadvertently counted as a single signal. The magnitude of this combined signal is greater than the individual components, leading to errors in later analysis.
The energy of an incident gamma-ray is generally represented by the amplitude of the corresponding pulse-like signal produced by the detector. The presence of specific gamma-ray energies within the detector signal is indicative of particular elements in the material from which gamma-rays originate. Thus, a failure to differentiate a large amplitude signal caused by a single scintillation event from the superposition of multiple events can have a serious effect on the accuracy of subsequent spectroscopic analysis.
Although the effects of pile-up have been described above in the context of photomultiplier detectors and gamma-ray detectors, they apply equally to other types of detectors for these and other forms of radiation, including x-ray detectors such as lithium-drifted silicon crystal detectors, and surface barrier detectors, for example. Additionally, as will be understood by those skilled in the art, a reference to “output of a detector” may include the output of a pre-amplifier connected to a basic detector component such as a lithium-drifted silicon or germanium crystal, or a bare surface barrier detector).
Some existing techniques aim to prevent corruption of the spectroscopic analysis due to pulse pile-up. Certain pulse shaping electronics have been shown to reduce the response time of the detector resulting in a diminished prevalence of pile-up in the final spectrum [A. Pullia, A. Geraci and G. Ripamonti, Quasioptimum γ and X-Ray Spectroscopy Based on Real-Time Digital Techniques, Nucl. Inst. and Meth. A 439 (2000) 378-384]. This technique is limited, however, by detector response time. Another approach is ‘pulse pile-up rejection’ whereby signals suspected to contain pulse pipe-up are discarded. Only signals free from pulse pile-up are used in spectroscopic analysis. However, as the rate of radiation incident on the detector increases, so too does the likelihood that pulse pile-up will occur and the more it is necessary to discard data. Accordingly, existing pulse pile-up rejection is of limited usefulness since a state is quickly reached beyond which a higher incident radiation flux ceases to reduce the time needed for analysis, as an increasing percentage of data must be rejected.
Moreover, the increasing ‘dead time’ during which no usable data is received but the sample continues to be irradiated results in the sample or material being analysed being subjected to a larger dose or fluence of radiation and is strictly necessary. In situations where the sample or material experiences radiation damage during analysis, this can be a serious consequence. Furthermore, in some circumstances (e.g., high energy particle physics experiments), the detectors themselves can be subject to substantial radiation damage, and the greater the dead time, the less useful data can be provided by such detectors during their lifetime.
Pulse pile-up is also a problem in seismic data collection; Naoki Saito (in Superresolution of Noisy Band-Limited Data by Data Adaptive Regularization and its Application to Seismic Trace Inversion, CH2847-2/90/0000-123, 1990) teaches a technique for resolving closely placed spikes in a seismic trace. The disclosed technique employs data adaptive regularization to recover missing frequency information in the presence of noise and, through repeated iteration, obtain improved resolution. However, this approach is computationally intensive.
It is desired to provide a method and apparatus for locating a pulse in detector output data that alleviate one or more difficulties of the prior art, or that at least provide a useful alternative.